The present invention is in the field of medical imaging and, more particularly, to methods and systems relating to positron emission tomography.
Medical imaging technology has made remarkable advances in recent years, including developments and improvements in computed tomography (“CT”), magnetic resonance imaging (“MRI”), functional magnetic resonance imaging (“fMRI”), single photon emission computed tomography (“SPECT”), and positron emission tomography (“PET”).
PET imaging has revolutionized imaging of internal biological regions by providing functional images of a patient or other region of interest. Positron emission tomography is a nuclear medicine medical imaging technique that produces a three-dimensional image or map of functional processes in the body, e.g., imaging that illuminates chemical and metabolic activity in the patient. The role of PET imaging in oncology research and patient care, in particular, is growing due to the ability of PET to add unique functional information to that obtained by conventional anatomical imaging modalities, for example CT.
PET scanning is an emissive technique wherein a short-lived radioactive tracer isotope, chemically combined with a metabolically active molecule such as a sugar, is injected into the subject. The metabolically active molecule becomes concentrated in the tissues of interest, concentrating the tracer isotope in regions of such activity. After injecting the isotope, the patient is placed on the scanner. As the injected isotope decays it emits a positron that annihilates with an electron, producing a pair of gamma rays or photons that travel in opposite directions. In general terms, the emitted photons are detected when they reach a scintillator material in the scanning device, creating a burst of light that is detected by photomultiplier tubes.
The detection technique relies on the coincident detection of the pair of photons to identify valid signals. Photons that are not detected within a few nanoseconds of each other are ignored. A straight line through the locations in the detector where the coincident photons are detected is called the line of response (“LOR”). The location of the positron emission is therefore known to lie somewhere along the LOR. The PET scanner uses the pair detection events and the LORs to map the density of the tracer isotope within the body. In a typical system, the images are generated along parallel slices separated by about 5 mm and the images are then combined to produce a three -dimensional image or model of the region of interest. The resulting map shows where the tracer isotope has become concentrated, identifying regions of metabolic activity in the body.
In most modem PET imaging systems, the PET scans are combined with CT scans, primarily to provide structural or anatomical information, to facilitate interpretation of the PET functional imaging. CT scans are a transmissive imaging technique wherein x-rays are transmitted through the region of interest and detected by detectors located generally opposite the x-ray source. The combination of PET scanning and CT scanning provides the medical professional with both anatomic and metabolic information for a patient. PET imaging is used heavily in clinical oncology (medical imaging of tumors and the search for metastases) and is also used in human brain and heart research.
The primary motivation in combining CT scanners and PET scanners is to obtain precise anatomical localization of regions identified on the PET tracer uptake images. A synergism with PET/CT scanners, however, is that the CT scanner data can be used to provide x-ray-based attenuation correction of the PET emission data, as discussed in more detail below.
Several physical effects can perturb tracer uptake images obtained with PET. The most significant of these effects are photon attenuation, scattered and random coincidences, detector efficiency variations, and scanner dead time. Of these, by far the most important is photon attenuation, which can affect both the visual quality and the quantitative accuracy of PET data. For example, in regions of non-uniform density, such as the thorax, the lack of attenuation correction can mask the appearance of solid lesions with moderately elevated tracer uptake.
The transmission of photons through any material can be characterized by a linear attenuation coefficient μ. The linear attenuation coefficient depends on the photon energy E and the molecular weigh or atomic number Z of the material through which the photon passes. The linear attenuation coefficient can be defined as the probability per unit path length that the photon will interact with the absorbing material (for example, patient tissue). Photon attenuation includes two types of interactions—absorption and scatter. Linear attenuation coefficients for absorption are proportional to the density of the absorber and it is therefore common to express the attenuation property of a material in terms of its mass attenuation coefficient μ/ρ, where ρ is the density of the material. The total attenuation coefficient for an interaction is given by the sum of the possible photon interaction mechanisms, which for diagnostic imaging, are primarily photoelectric absorption and Compton scattering.
The total photoelectric and Compton linear attenuation coefficients for muscle and bone, as a function of photon energy in the range of 10 to 1,000 keV, are illustrated in FIG. 1. The portions of the total attenuation from photoelectric absorption and from Compton scattering are also shown. It can be seen from FIG. 1 that the total attenuation is dominated by photoelectric absorption below photon energies of about 30 keV for muscle and below about 50 keV for bone, and is dominated by Compton scattering for photon energies between about 200 keV and 1,000 keV.
The linear attenuation coefficient for Compton scattering is proportional to the atomic number of the material that the photon passes through. The mass attenuation coefficient for Compton scattering is, therefore, essentially independent of the material. For this reason, the mass attenuation coefficient for different materials converges for photon energies between about 200 keV to 1,000 keV where Compton scattering dominates. However, x-ray radiograph imaging generally utilizes the energy range from about 30 to 130 keV, where the total attenuation is sensitive to both photoelectric absorption and Compton scatter. PET imaging, in contrast, occurs at 511 keV, where photon attenuation by biological materials is determined primarily by Compton scattering.
It will also be appreciated that, for other compounds, including, for example, body-equivalent plastics or body regions represented by combinations of air and soft tissue (e.g., lungs) or combinations of soft tissue and bone, the mass attenuation coefficient can be calculated according to the mixture rule:
      μ    ρ    =            ∑      i        ⁢                            w          i                ⁢                  μ          i                            ρ        i            where wi is the proportion by weight of the i-th constituent. The mixture rule is accurate to within a few percent for photon energies above about 10 keV.
The physical process of photon attenuation obviously affects annihilation photons that are produced and detected in PET emission imaging. Attenuation correction factors generally must be derived from transmission data, such as CT scans, to correct the PET data for photon attenuation. If the object has a simple geometry and is homogeneous, then the attenuation correction factors for PET can be calculated assuming an a priori estimate of the object's geometry and knowledge of the materials and their attenuation coefficients in the object. This method avoids the need to acquire transmissive data, but in practice is only marginally useful in relatively simple situations. This approach introduces biases and will not work in heterogeneous anatomical regions such as the thorax. In these more complex regions, measured attenuation factors are needed.
The distribution of attenuation coefficients in the object can be measured by using transmission data—for example, using positron, γ-ray, or x-ray sources. Comparing transmission scans with and without the patient in the field of view allows a direct estimate of the attenuation along each line of response (“LOR”).
With PET/CT scanners, a 511 keV attenuation map can be estimated from the CT image to correct the PET emission data for photon attenuation. There are four significant advantages of using CT to acquire transmission scans for attenuation correction of the PET emission data: First, the CT data has relatively low statistical noise as compared with transmission data acquired with radionuclide sources. Second, the CT scan data can be acquired much more quickly than a standard PET transmission scan. Third is the ability to collect uncontaminated post-injection transmission scans—an important practical consideration. Fourth, using x-ray transmission scanning eliminates the need for radionuclide transmission hardware and periodic replacement of the radionuclide sources. A potential benefit not yet fully explored is the direct incorporation of anatomical information derived from the CT data into the PET image reconstruction process.
However, as indicated in FIG. 1, the attenuation coefficient is also dependent on the energy of the photon. When used to correct PET emission data for photon attenuation, the data measured with x-ray CT must be converted to the appropriate attenuation coefficient values at 511 keV. Once the attenuation map at the correct energy is obtained, the attenuation correction factor for an individual sinogram element is calculated by numerically integrating the attenuation along the LOR corresponding to the emission sinogram element. Although x-ray-based attenuation correction introduces very little noise, it has increased potential for introducing bias in the reconstructed emission images, particularly when the scanned region contains contrast agents or metal objects, as discussed in more detail below. To understand why x-ray-based attenuation correction can cause bias, we first consider the data obtained in CT imaging.
CT numbers are generally obtained in Hounsfield units (HU) and cannot be directly used to correct the emission data for photon attenuation at 511 keV. The Hounsfield scale is a quantitative scale for describing radiodensity. Radiodensity is the property of relative transparency to the passage of X-rays through a material.
If the material properties of the imaged region are known, then conversion between the CT numbers and the desired attenuation coefficients can be readily obtained. However, in heterogeneous regions the material properties may be difficult to determine. There are three general methods for converting the CT numbers to attenuation coefficients-segmentation, scaling, and dual-energy CT scans.
Segmentation methods separate the CT image into regions corresponding to different tissue types (for example, soft tissue, lung, bone) and the CT number for each tissue type is then replaced with an attenuation coefficient based on the tissue type at a photon energy of 511 keV. A significant problem with this method, however, is that some tissue regions have varying densities and may not be accurately represented by a single attenuation factor. In pulmonary regions, for example, the density of lung tissue varies by as much as thirty percent.
Scaling generally provides a more accurate estimate of the attenuation coefficient. In general, for a particular tissue type the image values produced by CT are approximately linearly related to the physical attenuation coefficient of that tissue type. It is therefore possible to estimate the attenuation map of the patient simply by multiplying the entire CT image by the ratio of attenuation coefficients of water (representing soft tissue) at the photon energies of CT and PET. However, different scaling factors are needed for bone (relatively high-Z) and soft tissue (relatively low-Z) to transform CT images acquired at x-ray energy values to calculate an attenuation map calibrated at the emission energy of 511 keV.
One approach to compensate for the high-Z materials is to note that CT numbers having a radiodensity in the range of −1,000<HU<0 primarily represents regions containing lung and soft tissues, whereas regions having CT numbers >0 primarily contain mixtures of soft-tissue and bone. Therefore, a bilinear scaling can be used to convert image CT numbers to attenuation coefficients—for example, as indicated by dashed curve 90 in FIG. 2, wherein the CT number is converted to an attenuation coefficient along a bilinear curve having one slope for a CT number less than 0 and a piecewise continuous portion with a different slope for a CT number greater than 0.
An alternative approach for converting CT images to attenuation maps is the so-called “hybrid method,” which combines segmentation and scaling. Specifically, the attenuation map at 511 keV is estimated by first using a threshold CT number to approximately distinguish bone components in the CT image, and then using separate scaling factors for the mass attenuation coefficients of the bone and non-bone components. This hybrid method in converting CT numbers to linear attenuation coefficients is indicated by the piece-wise discontinuous curve 92 in FIG. 2, where the threshold for differentiating bone from non-bone regions was selected to be about 300 HU.
Although the hybrid method is not piece-wise continuous, unlike the bilinear method, there is no unique transformation from CT energies to 511 keV due to the possibility of independent variations in density and Z, which can cause two materials with similar CT numbers at some effective energy (say 70 keV) to have different attenuation coefficients at 511 keV. Conversely, it is possible for two distinct materials with the same value of attenuation coefficient at 511 keV to yield different CT numbers. Fortunately, both the bilinear scaling method and the hybrid method have been shown to give reasonable results for biological materials in practice. However, bias and other error can result when contrast agents or metal objects are present in the patient.
Dual energy x-ray imaging, in theory, provides an accurate solution to the problem of converting CT numbers to linear attenuation coefficients at 511 keV using a basis material decomposition approach. An exemplary state-of-the-art dual energy x-ray imaging method is disclosed in U.S. Pat. No. 6,754,298 to Fessler, which is hereby expressly incorporated by reference. This dual energy x-ray scanning disclosed by Fessler can be understood by regarding the attenuation coefficient as a weighted sum of photoelectric absorption and Compton scattering probabilities—in essence, a system with two components. If we were able to determine the attenuation due to the individual photoelectric and Compton components separately, they could be scaled separately to any energy and then added to obtain the total attenuation coefficient, as discussed above. A disadvantage of such an approach is that the dual-energy CT method calculates the attenuation map by forming a generalized subtraction of two separate CT scans in which the noise of the component CT scans adds in quadrature. Therefore, although existing dual-energy techniques potentially offer the highest degree of accuracy, they also can suffer from excessive noise.
For normal biological materials, the bilinear scaling method of x-ray-based attenuation correction for PET/CT scanners performs satisfactorily for clinical procedures. However, there is no unique transformation from CT energies to 511 keV when the examined region contains a complex mixture of material components having differing densities and molecular weights, such as tissue and CT contrast agents and/or metallic objects. A mismatch between the measured/calculated and true attenuation values can introduce biases and artifacts into the reconstructed PET image, particularly when contrast agent is present.